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Dataset results
14 results for “Dynamic social network”
Opinion dynamics in social network under competition: the role of influencing factors in consensus reaching
<p>The profitability of opinion and the finiteness of individual attention have already spawned the extensive competition for individual preferences on social networks. It's quite necessary to investigate the opinion dynamics over social networks in a competitive environment. To this point, this paper develops a novel social network DeGroot model based on competition game (DGCG) to characterize the opinion evolution in a competitive opinion dynamics. Based on the DGCG model, we obtain equilibrium results in the stable state of opinion evolution. Consecutively, we analyze what role relevant factors play in the final consensus and competitive outcomes, including the resource ratio of both contestants, initial opinions and network structure. Theoretical analyses and simulation experiments show that these factors can significantly sway the consensus and even reverse competition outcomes.</p>
Data from: Personality and social network structure influence cooperative dynamics across canid species
<p>In canids, cooperative behaviour occurs in many scenarios. However, most studies focus on single-species observations, not accounting for variation beyond the species-level. We modelled cooperative behaviour using Eigenvalue centrality as well as boldness combined with biological traits such as kinship, sex, age, mating system and foraging strategy in multiple canid species with Bayesian inference, Tukey HSD and distance correlation.</p>
Opinion dynamics in social network under competition: the role of influencing factors in consensus reaching
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Dynamic shifts in social network structure and composition within a breeding hybrid population
1. Mating behavior and the timing of reproduction can inhibit genetic exchange between closely related species; however, these reproductive barriers are challenging to measure within natural populations. Social network analysis provides promising tools for studying the social context of hybridization, and the exchange of genetic variation, more generally. 2. We test how social networks within a hybrid population of California (Callipepla californica) and Gambel's quail (Callipepla gambelii) change over discrete periods of a breeding season. We assess patterns of phenotypic and genotypic assortment, and ask whether altered associations between individuals (association rewiring), or changes to the composition of the population (individual turnover) drive network dynamics. We use genetic data to test whether social associations and relatedness between individuals correlate with patterns of parentage within the hybrid population. 3. To achieve these aims, we combine RFID association data, phenotypic data, and genomic measures with social network analyses. We adopt methods from the ecological network literature to quantify shifts in network structure and to partition changes into those due to individual turnover and association rewiring. We integrate genomic data into networks as node-level attributes (ancestry) and edges (relatedness, parentage) to test links between social and parentage networks. 4. We show that rewiring of associations between individuals that persist across network periods, rather than individual turnover, drives the majority of the changes in network structure throughout the breeding season, and that the traits involved in phenotypic/genotypic assortment were highly dynamic over time. Social networks were randomly assorted based upon genetic ancestry, suggesting weak behavioral reproductive isolation within this hybrid population. Finally, we show that the strength of associations within the social network, but not levels of genetic relatedness, predict patterns of parentage. 5. Social networks play an important role in population processes such as the transmission of disease and information, yet there has been less focus on how networks influence the exchange of genetic variation. By integrating analyses of social structure, phenotypic assortment, and reproductive outcomes within a hybrid zone, we demonstrate the utility of social networks for analyzing links between social context and gene flow within wild populations. 08-Jul-2020
Data from: Linking social and spatial networks to viral community phylogenetics reveals subtype-specific transmission dynamics in African lions
1.Heterogeneity within pathogen species can have important consequences for how pathogens transmit across landscapes; however, discerning different transmission routes is challenging. 2.Here we apply both phylodynamic and phylogenetic community ecology techniques to examine the consequences of pathogen heterogeneity on transmission by assessing subtype specific transmission pathways in a social carnivore. 3.We use comprehensive social and spatial network data to examine transmission pathways for three subtypes of feline immunodeficiency virus (FIVPle) in African lions (Panthera leo) at multiple scales in the Serengeti National Park, Tanzania. We used FIVPle molecular data to examine the role of social organization and lion density in shaping transmission pathways and tested to what extent vertical (i.e., father and/or mother offspring relationships) or horizontal (between unrelated individuals) transmission underpinned these patterns for each subtype. Using the same data, we constructed subtype specific FIVPle co-occurrence networks and assessed what combination of social networks, spatial networks, or co-infection best structured the FIVPle network. 4.While social organization (i.e., pride) was an important component of FIVPle transmission pathways at all scales, we find that FIVPle subtypes exhibited different transmission pathways at within- and between-pride scales. A combination of social and spatial networks, coupled with consideration of subtype co-infection, was likely to be important for FIVPle transmission for the two major subtypes, but the relative contribution of each factor was strongly subtype specific. 5.Our study provides evidence that pathogen heterogeneity is important in understanding pathogen transmission, which could have consequences for how endemic pathogens are managed. Furthermore, we demonstrate that community phylogenetic ecology coupled with phylodynamic techniques can reveal insights into the differential evolutionary pressures acting on virus subtypes, which can manifest into landscape-level effects.
Data from: Linking social and spatial networks to viral community phylogenetics reveals subtype-specific transmission dynamics in African lions
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Dynamic shifts in social network structure and composition within a breeding hybrid population
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Data from: Co-prescription network reveals social dynamics of opioid doctor shopping
This paper examines network prominence in a co-prescription network as an indicator of opioid doctor shopping (i.e., fraudulent solicitation of opioids from multiple prescribers). Using longitudinal data from a large commercially insured population, we construct a network where a tie between patients is weighted by the number of shared opioid prescribers. Given prior research suggesting that doctor shopping may be a social process, we hypothesize that active doctor shoppers will occupy central structural positions in this network. We show that network prominence, operationalized using PageRank, is associated with more opioid prescriptions, higher predicted risk for dangerous morphine dosage, opioid overdose, and opioid use disorder, controlling for number of prescribers and other variables. Moreover, as a patient's prominence increases over time, so does their risk for these outcomes, compared to their own average level of risk. Results highlight the importance of co-prescription networks in characterizing high-risk social dynamics.
Information diffusion assumptions can distort our understanding of social network dynamics (code and data)
<p>This repository contains the data (<code>cascade_reconstruction.tar.gz</code>) and code (<code>code_repository.tar.gz</code>) for a paper titled "Information diffusion assumptions can distort our understanding of social network dynamics" by <a href="https://www.matthewdeverna.com/">Matthew R. DeVerna</a>, <a href="https://pierri.faculty.polimi.it/">Francesco Pierri</a>, <a href="https://rachithaiyappa.github.io/">Rachith Aiyappa</a>, <a href="https://diogofpacheco.github.io/">Diogo Pachecho</a>, <a href="https://jbryden.co.uk/home/">John Bryden</a>, and <a href="https://cnets.indiana.edu/fil">Filippo Menczer</a> .</p> <p>Please see the README.md file for important details! If you would like to report issues with the code, you can do so through an associated GitHub repository that houses the project's code, which can be found <a href="https://github.com/osome-iu/cascade_reconstruction">here</a>.</p>
Data from: The index case is not enough: variation among individuals, groups, and social networks modify bacterial transmission dynamics
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Data from: Co-prescription network reveals social dynamics of opioid doctor shopping
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Data from: Similar but different: dynamic social network analysis highlights fundamental differences between the fission-fusion societies of two equid species, the onager and Grevy's zebra
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Using a real-world network to model the trade-off between stay-at-home restriction, vaccination, social distancing and working hours on COVID-19 dynamics
<p>These datasets have been obtained through thousands of well-carried simulations by using the agent-based model based on a time-dynamic graph with stochastic transmission events. </p> <p>These simulations have been conducted on MATLAB 2019a.</p>
Decision Analysis in e-Cognocracy using Dynamic Social Networks
<p>Poser presented to the ICDSST 2020 Conference, International Conference on Decision Support System Technologies, Zaragoza (Spain), May 21-23 2020.</p>
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OpenNeuro
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